Function-based Object Model for Use in WebSite Adaptation

ABSTRACT

By understanding a website author&#39;s intention through an analysis of the function of a website, website content can be adapted for presentation or rendering in a manner that more closely appreciates and respects the function behind the website. Various inventive systems and methods analyze a website&#39;s function so that its content can be adapted to different client environments, e.g. devices, network conditions, or user preferences. A novel function-based object model automatically identifies objects associated with a website, and analyzes those objects in terms of their functions. The function-based object model permits consistent, informed decisions to be made in the adaptation process, so that web content is displayed not only in an organized manner, but in a manner that reflects the author&#39;s intention.

RELATED APPLICATIONS

This is a continuation application which claims priority to commonlyassigned co-pending U.S. patent application Ser. No. 09/893,335(Applicant Docket No. MS1-0913US), entitled “Function-based Object Modelfor Use in WebSite Adaptation” to Chen et al., filed on Jun. 26, 2001,which is incorporated by reference herein for all that it teaches anddiscloses.

TECHNICAL FIELD

This invention relates to methods and systems for adapting websites forpresentation or rendering on different devices.

BACKGROUND

The increasing diversity in terms of devices, protocols, networks anduser preferences in today's web has made adaptive capability criticalfor Internet applications. The term “adaptive capability” means havingthe ability to take web content presented in one form (such as thatwhich would be presented in the form of a website on a desktop computer)and process it to present or display it in another form (such as thatwhich would be presented on a handheld device).

To achieve adequate adaptation, it can become crucial to understand awebsite's structure and content function, as intended by the author ofthat website. Most of the previous works in this particular area achieveadaptation only under some special conditions due to the lack ofstructural information. Some works have attempted to extract semanticstructural information from HTML tags either manually or automatically.These approaches, however, lack an overview of the whole website. Inaddition, these approaches are only suitable for HTML content.Furthermore, most of the approaches do not work effectively even forHTML pages because HTML was designed for both presentational andstructural representation of content. Further misuses of structural HTMLtags for layout purpose make the situation even worse. Cascade StyleSheets (as set forth in the W3C) attempts to compensate for thissituation by representing the presentation information separately, butits application is quite limited. Moreover, the difficulty of extractingsemantic structure from HTML tags is still not solved by Cascade StyleSheets. Accordingly, the results of previous semantic rule-basedapproaches for HTML content are not very stable for general web pages.

Smith et al., in Scalable Multimedia Delivery for Pervasive Computing,Proc., ACM Multimedia 99, 1999, pp. 131-140, proposed a so-calledInfoPyramid model to represent the structural information of multimediacontent. However, the InfoPyramid model does not exist in current webcontent. XML provides a semantic structural description of content byDocument Type Description (DTD). However, a DTD is not a generalsolution because each application area would necessarily require its ownspecial DTD. Additionally, XML does not take into consideration thefunction of content. Additionally, although Extensible StylesheetLanguage (as set forth in the W3C) provides a flexible way of presentingthe same content in different devices, it needs be generated manually,which would be a labor-intensive work for authors.

Accordingly, this invention arose out of concerns associated withproviding improved methods and systems for website adaptation.

SUMMARY

In accordance with the described embodiments, a function-based objectmodel (FOM) for website adaptation is described. The function-basedobject model attempts to understand an author's intention that underliesan authored website. It does so by identifying and using objectfunctions and categories. In accordance with FOM techniques, a websiteis analyzed to identify objects that are associated with that website.The objects are then classified as basic objects (BO) and compositeobjects (CO). Each object comprising part of a website serves certainfunctions. These functions are defined as either basic functions orspecific functions. The functions reflect an author's intentionregarding the purpose of a particular object.

Based on this observation, the FOM model includes two complementaryaspects: a so-called Basic FOM and a Specific FOM. The basic FOMrepresents an object by its basic functional properties, and thespecific FOM represents an object by its category. Combining the BasicFOM and the Specific FOM together, a thorough understanding of anauthor's intention regarding a website can be ascertained. The describedembodiments can provide an automatic approach for detecting thefunctional properties and category of an object for FOM generation.

FOM provides two level guidelines for web content adaptation: generalrule-based on Basic FOM, and specific rules based on Specific FOM.Through the rule-based approach, a website can thus be automaticallyadapted in a manner that preserves, to a desirable degree, the author'soriginal intention with respect to the website.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram that illustrates two exemplary objects inaccordance with the described embodiments.

FIG. 2 is a diagram of an exemplary web page that illustrates exemplaryobjects in accordance with one or more embodiments.

FIG. 3 is a diagram of an exemplary composite object, and illustratesvarious objects that comprise the composite object.

FIG. 4 is a diagram of an exemplary full representation in accordancewith one embodiment.

FIG. 5 is a flow diagram of a decision-making process in accordance withone or more embodiments.

FIG. 6 is a graph that is useful in understanding aspects of one or moreembodiments.

FIG. 7 is a graph that is useful in understanding aspects of one or moreembodiments.

FIG. 8 is a graph that is useful in understanding aspects of one or moreembodiments.

FIG. 9 is a flow diagram of steps in a method in accordance with oneembodiment.

FIG. 10 is a diagram of an exemplary web page, and a diagrammaticrepresentation of so-called decks that have been provided through aninventive adaptation process.

FIG. 11 is a diagram of an exemplary web page, and a diagrammaticrepresentation of so-called decks that have been provided through aninventive adaptation process.

FIG. 12 is a diagram that is useful in understanding aspects of one ormore described embodiments.

FIG. 13 is a diagram that is useful in understanding aspects of one ormore described embodiments.

FIG. 14 is a diagram that is useful in understanding aspects of one ormore described embodiments.

FIG. 15 is a block diagram of an exemplary computer architecture inaccordance with one or more embodiments.

FIG. 16 is a diagram that diagrammatically illustrates web content inone format that has been converted to a different format, which, in thisparticular example, is in a format for presentation on a WAP-enableddevice.

FIG. 17 is a diagram of an exemplary web page, and a diagrammaticrepresentation of so-called decks that have been provided through aninventive adaptation process.

FIG. 18 is a block diagram of an exemplary computer environment in whichvarious embodiments can be practiced.

DETAILED DESCRIPTION Overview

By understanding a website author's intention through an analysis of thefunction of a website, website content can be adapted for presentationor rendering. In the context of this document, the terms “presentation”and “rendering”, as such pertains to the display of content such as awebpage, are used interchangeably. Adaptation can take place in view ofdifferent client environments (devices, networking conditions such asmodem and LAN, and user preferences such as browsing for long term andshort term goals) to name just a few. Adaptation can thus be effected ina manner that more closely appreciates and respects the function behindthe website. Various systems and methods are described below thatanalyze a website's function so that its content can be adapted tovarious devices. A novel function-based object model automaticallyidentifies objects associated with a website and analyzes those objectsin terms of their functions. The function-based object model permitsconsistent, informed decisions to be made in the adaptation process sothat web content is displayed not only in an organized manner, but in amanner that reflects the author's intention.

Function-Based Object Model

In the described embodiments, an “object” is the basic element of ahypermedia system and comprises a piece or a set of information thatperforms certain functions. According to the number of component objectsan object contains, objects can be classified as basic objects andcomposite objects. In the discussion that follows, two function-basedobject models are described—(1) the basic function-based object modeland (2) the specific function-based object model. The basicfunction-based object model is described in the context of both basicobjects and composite objects. The specific function-based object modelis discussed in the context of providing object categories that directlyreflect a website author's intention. Such will become more apparent asthe description below is read.

Basic Function-Based Object Model of a Basic Object

In a hypermedia system, a “basic object” is the smallest informationbody that cannot be further divided. Only as a whole can it performcertain functions. In the HTML context, a basic object is defined by aset of HTML tags that enclose no additional HTML tags. A basic objectcan perform or be associated with one or more of the following basicfunctions. It can provide some semantic information to users (i.e.provide some user-understandable meaning), guide users to other objectsvia a hyperlink, beautify or otherwise provide some type of visuallyperceptible and/or pleasing effect on a page, or have an associatedinterface for users to interact or otherwise communicate with thesystem.

In accordance with the above-mentioned functions of the basic object, abasic object can be considered as having the following properties, whichare also set forth in FIG. 1.

-   -   Presentation: defines the way that a basic object shows itself        to or is otherwise presented to users. Presentation properties        can include Media Type, Layout Format and Encoding Format, each        of which can be assigned values as will become apparent below.    -   Semanteme: the content meaning of a basic object. Since XML has        a good scheme for describing the semantic meaning of contents,        here semanteme is more at semantic layer such as Keyword,        Headline, Abstract and Content instead.    -   Decoration: pertains to the extent to which a basic object        serves to beautify or decorate the webpage. A decoration value        can be assigned to a basic object and is indicated as x,        xε[0,1]. The higher the value of x, the more an object serves        for decoration. If x=1, the basic object serves only a        decoration function, without any other information. If x=0, the        basic object has no decoration function.    -   Hyperlink: pertains to the object a basic object points to, and        which has the following cases: (1) No Hyperlink, (2) Hyperlink        to Other Object and (3) Hyperlink to Other Application.    -   Interaction: pertains to the interaction method of a basic        object, and which has the following cases: Display (for        presenting information), Button (for selecting list item or        submitting information) and Input (for inputting information).

Accordingly, based on the properties described above, the function-basedobject model of a basic object can be represented as follows:

Basic Object (Presentation, Semanteme, Decoration, Hyperlink,Interaction)

FIG. 2 shows a web page 200 in the form of an index page that comprisesmultiple different objects 202-224, at least some of which comprisebasic objects. These objects do not constitute all of the objectsembodied by the web page. Rather, the enumerated basic objects are forillustrative purposes only.

As an example of a function-based object model, the function-basedobject model of basic object 214 can be described as follows:

-   -   Presentation:        -   Layout Format: Left Aligned . . .        -   Media Type: Text        -   Encoding: Language: English, Content Type: Text/HTML . . .    -   Semanteme: Abstract    -   Hyperlink: No Hyperlink    -   Decoration: 0    -   Interaction: Display

Basic Function-Based Object Model of a Composite Object

In the illustrated and described embodiment, a “composite object”comprises a set of objects (either basic objects or other compositeobjects) that perform some certain functions together. These objects arecombined under some basic clustering rules. Since a web page is composedof composite objects and basic objects, and a website is a set of webpages, websites and web pages can themselves be composite objects.

In accordance with the described embodiment, the notion of a fullrepresentation is used to describe a tree-like structure that representsa composite object that has been unfolded to ascertain all of thechildren that comprise basic objects. As a composite object can itselfcontain other composite objects, this unfolding process can be arepeated process until all of the children comprising basic objects arediscovered. A “root child” is a child that connects with the rootdirectly. Root children are said to be “brother objects” to each other.

With respect to the functions of a composite object, such objects canhave all of the functions of a basic object. Composite object also haveadditional functions. Specifically, composite objects can have aclustering function. The root children of a composite object areclustered based on some basic rules to perform certain goals thatreflect an author's intention regarding the relationship and hierarchyof the root children.

Based on the clustering function, a composite object has its basicproperties as follows and as set forth in FIG. 1:

-   -   Clustering Relationship        -   Complement: root children of a composite object are            complementary to achieve a goal, and, they have different            basic properties.        -   Parallel: root children of a composite object are of equal            importance in achieving a goal, and, they generally have the            same basic properties. If the root children have both            similar and different properties, their relationship will be            calculated by a weighted sum of the similarity of these            properties. Then, a threshold will be set to decide whether            they are complementary or parallel.        -   Table: root children of a composite object can be clustered            into parallel root children according to two semantic            dimensions (normally row/column headers of a table).    -   Presentation Relationship: presentation order (time and space)        of root children inside a composite object, and whether the root        children are separable when they are presented. That is, whether        the components should be displayed at the same time or different        times, and whether they should be displayed as a whole or not.

Based on the properties described above, the function-based object modelof a composite object is as follows:

CO={O_(i), Clustering Relationship, Presentation Relationship|O_(i) isthe Root Children of the CO, i=, 1, 2, . . . , N_(R)}, where N_(R) isthe total number of Root Children of the CO.

To assist in further understanding composite objects, the reader isreferred to FIG. 3. There, various objects within and comprising part ofcomposite object 210 are designated respectively at 210 a, 210 b, 210 c,and 210 d. The function-based object model for object 210 is as follows:

-   -   Root Children: 210 a, 210 b, 210 d    -   Clustering Relationship Complement    -   Presentation Relationship Vertical; Separable

FIG. 4 shows a somewhat abbreviated full representation of object 210.There, the composite objects are designated by the darker boxes. Noticethat the various composite objects are broken down into their basicobject constituent parts. For example, notice that root object 400comprises three root children 402, 404, and 406 correspondingrespectively to objects 210 a, 210 b, and 210 d. Child 404 comprisesfour children (408, 410, 412, and 414), each of which are compositeobjects themselves. Child 410 comprises two children—one child 416corresponds to a basic object, the other child 418 corresponds to acomposite object. Child 418, in turn, has two children 420, 422, each ofwhich comprises a basic object.

Specific Function-Based Object Model—Category of an Object

In accordance with the described embodiment, the specific function of anobject in a given application environment is represented by itscategory, which reflects an author's intention directly. There can bemany object categories according to various purposes. In the discussionbelow, the HTML content of the FIG. 2 web page is utilized as an exampleto describe various object categories.

EXEMPLARY OBJECT CATEGORIES

-   -   Information Object: presents content information. An example of        an information object is object 214.    -   Navigation Object: provides a navigation guide. An example of a        navigation object is object 218. In addition, there are        different sub-categories of navigation objects as follows:        -   Navigation Bar: a composite object with parallel navigation            objects as root children. The composite object exists in a            set of web pages in the website to provide a global            navigation guide. A navigation bar has the following            formats: Normal Navigation Bar, Frame, Menu (e.g. object            220) and Map.        -   Navigation List: a composite object with parallel navigation            objects as root children. The composite object exists only            in a single web page to provide local navigation guide. A            navigation list has the following format: Normal Navigation            List (object 208), Informative Navigation List (object 210),            Narrative Navigation List and Map List. In an Informative            Navigation List, each navigation object is followed by an            information object as an introduction. In a Narrative            Navigation List, all navigation objects are embedded in a            piece of narrative information.        -   Independent Navigation Guide: an object with a hyperlink            property and/or introductory information to provide a            navigation guide to a certain piece of content. An            independent navigation guide generally has weak relationship            with other objects around it. An example of an independent            navigation guide is object 222.    -   Interaction Object: provides user side interaction and has the        following formats: User Selection (for selecting items from a        list of available information), User Query (for inputting query        information, e.g. object 206) and User Submission (for uploading        information).    -   Decoration Object: serves for decoration purpose only (e.g.        object 204) and can have the following format: Separator (e.g.        object 224), List Leader (e.g. object 212), Highlight (e.g.        object 216) and Background    -   Special Function Object: performs special functions such as AD        (advertising), Logo, Contact, Copyright, Reference, etc.    -   Page Object: serves as the basic document of a website for        presenting related information and has two basic sub-categories:        Index Page and Content Page.        -   Index Page: serves mainly as navigation guide to other            pages. The web page of FIG. 2 is an example of an index            page.        -   Content Page: delivers semantic information to the user.

Automatic Function-Based Object Model Analysis for HTML Websites

Although it is desirable, in the authoring phase, for authors to addadditional information for purposes of assisting in the generation offunction-based object models, authors actually tend to not do so. Inaddition, many authors would likely prefer to not be burdened with suchextra tasks. Thus, it becomes important, in some embodiments, toautomatically analyze the function of content in a website. In thediscussion below, an automatic method for generating basic and specificfunction-based object models, such as those described above, isdescribed. Although the discussion is focused on HTML websites, it is tobe appreciated and understood that the described approach can beextended to other languages.

Basic Function-Based Object Model Generation

Before a basic function-based object model (such as that which isdescribed above) is generated, the objects are first detected. In HTMLcontent, a basic object is a non-breakable element within two tags, oran embedded Object. There is no other tag inside the content of a basicobject. According to this criteria, it is a fairly simple task toascertain all of the basic objects inside or comprising a website.

Based on the observation that objects in the same category generallyhave consistent visual styles, and they are separated by apparent visualboundaries from objects in other categories, composite objects can bedetected by conducting a layout analysis of a web page.

Any suitable object detection techniques can be used. In the discussionthat follows, an exemplary method for automatically analyzing thestructure of HTML pages based on detecting visual similarities ofobjects is described. It is to be appreciated and understood that thedescribed approach constitutes but one exemplary way in which this canbe done.

Visual Similarity of HTML Objects

In the HTML environment, it is fairly common for content to be dividedinto categories where each category holds records of similar or relatedsubtitles. In addition, records in one category are normally organizedin a manner having a consistent layout style. The basic idea of theapproach about to be described is to detect these visual cues, recordsand categories. In this specific context of object detection, thefollowing terms will be used:

-   -   Basic object: Non-breakable visual HTML objects that do not        include other tags (such as texts or tags as <IMG>, <HR>) or are        representations of one embedded media object.    -   Composite object: An ordered set of objects that consists of at        least one basic object or other composite object and these        objects must be adjacent if they are rendered. The order of        these elements is normally defined by reading habits. In        following discussions, we represent a composite object C as a        string of elements {e₁, e₂, . . . , e_(n)}, where e_(i)        comprises basic objects or other composite objects.    -   Group object: Special composite objects where all elements are        basic objects and these elements are rendered on the same text        line without deliberate line breaks by visual browsers.    -   List object: Special composite objects where all elements        satisfy some consistency constraint.    -   Structured Document: documents converted to hierarchical        structures of composite objects.

Visual Similarity of Basic Objects

During object detection, the HTML document is first parsed. During theparsing process, when identifying basic objects, rendering parametersare extracted by keeping a stack of tags that affect text attributeslike font face, styles, size, and color. For other embedded mediaobjects like images, information is extracted from tag attributes, or byanalyzing their file headers. According to these parameters, fuzzycomparison rules are defined that assist in deciding visual similarity.Table 1 immediately below provides a few examples of some fuzzycomparison rules that can be used for text objects, in which x is thesimilarity between objects.

TABLE 1 Starting from x = 1.0Compare  key  attributes  (like  <H 1>  …  <H 6>, <A>):$x = {x \cdot \left\{ \begin{matrix}{{Key\_ Modifier},} & {{Not}\mspace{14mu} {Equal}} \\{1,} & {Equal}\end{matrix} \right.}$${{Compare}\mspace{14mu} {font}\mspace{14mu} {size}\mspace{14mu} {attribute}\text{:}\mspace{14mu} x} = {x \cdot \left\{ \begin{matrix}{Size\_ Modifier} & {{Not}\mspace{14mu} {Equal}} \\{1,} & {Equal}\end{matrix} \right.}$ . . .${{Compare}\mspace{14mu} {text}\mspace{14mu} {length}\text{:}\mspace{14mu} x} = {x \cdot \left( \frac{\min \left( {{{length}\; 1},{{length}\; 2}} \right)}{\max \left( {{{length}\; 1},{{length}\; 2}} \right)} \right)^{{Adjust}\_ {factor}}}$

Visual Similarity of Composite Objects

The visual similarity of composite objects is based on that of basicobjects. To keep appropriate semantic granularities, group objects aredefined as content that is considered tightly related from our visualcue-based view (such as sentences and paragraphs). Group objects are notbroken up during the analysis. A basic object is treated as a compositeobject with only one element when it is compared with other compositeobjects. In addition, list objects have their specialties because we usethem to represent detected categories and records. And instead of usingwhole objects, we pick typical elements from list objects to comparewith others.

In the illustrated example, two kinds of visual similarity measurementsare defined:

-   -   Approximate Similarity: Comparison of two strings that enables        weighted mismatches and omissions.    -   Parallel Similarity: Comparison of two strings that enables only        weighted mismatches.

From the definitions above, it will be appreciated that an approximatesimilarity is more robust than a parallel similarity, if there areoutliers in strings. Parallel similarity can simply be an O(n)one-by-one comparison. Approximate similarity can be a bit more complex.Pseudo code of a suitable approximate similarity measurement algorithmis listed below in Table 2, and will be understood by those of skill inthe art. In the solution, dynamic programming is used to solve theproblem.

TABLE 2 Approximate String Compare Algorithm compareItem(x, NULL) =skip_weight(x); compareItem(simpleX, simpleY) = defined by Table 1;compareItem(strI[1..lthI], strJ[1..lthJ]) { dim cmp[0..lthJ]; cmp[0] =1; lastv10 = 1; for(j=1; j<=lthJ; j++) { cmp[j] = cmp[j-1] *compareItem(NULL, strJ[j])); } for(i=1; i<=lthI; i++) { lastv11 =cmp[0]; cmp[0] = lastv10 * compareItem(strI[i], NULL); lastv10 = cmp[0];for(j=1; j<=lthJ; j++) { v11 = lastv11 * compareItem(strI[i], strJ[j]);v10 = cmp[ j ] * compareItem(strI[i], NULL ); v01 = cmp[j-1] *compareItem(NULL, strJ[j]); lastv11 = cmp[j]; cmp[j] = max(v11, v10,v01); } } return cmp[lthJ]; }

Pattern Detection and Construction of Document Structures

Visual similarity patterns do not appear as very stable forms even withso-called “well composed” web pages. Their lengths can change, andoutliers in sequences are common. In addition, typically there are notknown boundaries to separate potential patterns. In the approach aboutto be described, we start from an exact pattern detection method basedon suffix trees, and then we expand exact patterns according toapproximate similarity. Each time a composite object is constructed, itis checked for potential patterns. These patterns are then converted tolist objects. Adjacent list objects are checked for visual similaritiesand are merged if they are similar.

In the discussion that follows, some of the terms that are used aredefined as follows. For composite object C={e₁, e₂, . . . , e_(n)}, anobject o is represented by a sub-string of C as {e_(s), . . . ,e_(s+l−1)}. Visual pattern p is represented as a set of “equal” objects{o_(l), . . . , o_(m)} and sometimes represented by a typical elemento_(p) of the pattern. We also follow some heuristics as listed below forlocating possible patterns.

-   -   Equal Judgment Two objects are equal only if their similarity        measurement is above a threshold E_(p).    -   Minimal Frequency One pattern must contain at least F_(p)        objects.    -   No Overlap Objects in one pattern do not overlap with each        other.    -   Alignment: Objects in one pattern are normally aligned tidily        (no zigzags).    -   Paragraphs: Content that resides in the same unbroken text line        should be tightly related and thus will be treated as one        element.    -   Minimal Deviation Standard deviations of objects' distributions        (positions) and lengths in potentially better patterns should be        smaller.    -   Maximum Coverage The potentially better patterns should have        bigger coverage of elements in C.    -   Sub-pattern Replacement: If all objects in a pattern are        concatenations of “equal” sub strings (sub-pattern), then these        objects are expanded to sub-strings. Assume a pattern as        {{e_(l), . . . , e_(m)}, {e_(m+l), . . . , e_(m+k)}, . . . } and        e_(i)==e_(j), ∀i,j, then the pattern is expanded to {e_(l), . .        . , e_(m), e_(m+l), . . . , e_(m+k), . . . }.    -   Significant Token Records in one category should have similar        prefix elements.

Quantization

To reduce the complexity of frequency counting, we first clustercandidate elements according to similarity measurements between eachelement. These clusters are then labeled with unique identifiers.Elements in the same cluster are assigned with the same identifier, andare considered as equal to each other. A clustering algorithm such asthe one described in Easter et al., A Density-Based Algorithm forDiscovering Clusters in Large Spatial Databases with Noise”, In ProcKDD'96, 1996, can be used because we do not know the number of possibleclusters at the beginning. Another reason is that our heuristics havespecified two values (E_(p) and F_(p)) that are just the epsilon andminimal density.

-   -   Eps-neighbourhood: N_(Eps)(e)={e′εC|similarity (e,e′)≧E_(p)},        where E_(p) is from “equal judgment”. (It will be the same as        originally defined in Easter et al., if we use        1/similarity(e,e′)≦1/E_(p) as the condition.)    -   Core point condition: |N_(Eps)(e)|≧F_(p), where F_(p) is defined        by “minimal frequency”.

For C={e₁, e₂, . . . , e_(n)}, if the clustering result is m clusters asT₁={e_(a), e_(b), . . . , e_(x)}, . . . T_(m)={e_(s), e_(t), . . . ,e_(y)}, we construct a token string T={t₁, t₂, . . . , t_(n)} with t_(i)equal to the cluster identifier that e_(i) belongs to. The token stringis then passed to the frequency counting stage. In following discussionswe use an example as C={e₁, e₂, . . . , e₁₃} and clustering result asT={C, A, B, D, A, B, E, D, A, B, C, A, B} with 4 clusters labeled asABCD and one outlier labeled as E. (In this illustrated example, aminimal frequency of 3 is selected. Thus only AB can be clusters and CDEare all noise.)

Frequency Counting

Frequencies of quantized patterns are counted efficiently using a suffixtree representation of token string T. Starting from the root node, the“label of path” of a node is actually what we called a “pattern”, andleaves under the node are positions of the pattern in a string. Thenumber of leaves under each node is the frequency of the pattern. Table3 below gives an example of pattern counting. A suitable algorithm tocreate the suffix tree is described in Ukkonen, On-line Construction ofSuffix Trees, Algorithmica, 14(3), September 1995, pp. 249-260.

TABLE 3 Pattern frequency counting of sequence ’CABDABEDABCAB'

Selection and Confirmation

From the results of the frequency counting, the best patterns areselected based on heuristics. Using Table 3 as an example, patterns {A,B} and {B} are good candidates. And {A, B} is superior to {B} accordingto the heuristic “maximum coverage”. However {A, B} can only cover apart of the elements because of outliers such as {C, D, E}. To cope withthese outliers these patterns are expanded based on approximatesimilarity measurements and the heuristic “significant token”. Currentlya naïve method is used—starting from a strict pattern, we try to appendsucceeding elements after each object of the pattern. The consistency ofthe pattern is checked during the process and it stops if an appendantbreaks the consistency. To illustrate the process, the steps ofexpanding pattern {A, B} are listed as follows:

{e₁, {e₂, e₃}, e₄, {e₅, e₆}, e₇, e₈, {e₉, e₀}, e₁₁, {e₁₂, e₁₃}}--> theoriginal pattern {A,B}{e₁, {e₂, e₃, e₄}, {e₅, e₆}, e₇, e₈, {e₉, e₁₀}, e₁₁, {e₁₂, e₁₃}}--> oneelement appended

. . .

{e₁, {e₂, e₃, e₄}, {e₅, e₆, e₇}, e₈, {e₉, e₁₀, e₁₁}, {e₁₂, e₁₃}}-->final result

From the example we can see that heuristic “significant token” mightsometimes miss possible patterns such as {{e₁, e₂, e₃}, {e₄, e₅, e₆,e₇}, {e₈, e₉, e₁₀}, {e₁₁, e₁₂, e₁₃}}, which do not have a “significanttoken” at the beginning.

Construction of a Structured Document

Structured documents are constructed in a recursive manner. Startingfrom basic objects and group objects, these elements are divided intopotential composite objects roughly based on block-level tags. Then, thepattern detection algorithm is applied to elements of these potentialcomposite objects, and detected patterns are converted to list objects.For example, using composite object and patterns of the section entitled“Selection and Confirmation” above, a new composite object can becreated as {e₁, {{e₂, e₃, e₄}, {e₅, e₆, e₇,

, {e₉, e₁₀, e₁₁}, {e₁₂, e₁₃}}} where the underscored element is a listobject. Note that outliers between two list elements are appended asdo-not-cares. The composite objects are then expanded to upper levels bymerging objects on the same level if they are not enclosed in importantstructures. After expanding, a check is performed to ascertain whethertwo adjacent list objects are similar and, if so, they are merged intoone. The whole process then repeats until <BODY> of HTML document hasbeen processed. The final composite object is the structured document.

Special Considerations for HTML Tables

In this section, application of the above-described visual cue-basedmethod for analyzing structures of HTML tables is described. Tables arethe most frequently used layout tools of HTML pages. From regular datatables to general content layouts, tables provide a powerful way tocontrol positions and alignments. Typical approaches such as thatdescribed in Hammer et al., Extracting Semistructured Information fromthe Web, Proc. Workshop on Management of Semistructured Data(PODS/SIGMOD'97), May 1997, require manually specifying rules andpattern strings to locate wanted data. Further, methods such as thosedescribed in Lim et al., An Automated Approach for RetrievingHierarchical Data from HTML Table, In Proc. CIKM'99, 1999, Kansas City,Mo., pp. 466-474, take further steps by automatically analyzing datatables with titles and headers. These approaches, however, do notautomatically decide if a table is data table.

As data tables are normally organized tidily, they should hold verystrong visual similarity patterns. In addition, many general contenttables also hold strong visual cues. The alignment nature of tables isthus used as a starting point for structural analysis. We start bycounting the rows and columns of a table. All empty rows and columns arestripped, since these are only for spacing and other layout purposes.Subsequently, we check for rows and columns because column-wise androw-wise organizations are quite common for data tables. The first checkdetermines whether the table gets heading and footing rows and columns(such as that specified by <TH> <THEAD> <TFOOT> tags). These tags arenormally used when the table is a column-wise or row-wise data table.Then, the elements in rows and columns are compared to check ifsimilarity consistency holds. If none of the above checks is successful,a more aggressive method is used. Specifically, the table is dividedinto smaller rectangular blocks and these blocks are checked forsimilarity consistency. The table is passed back to the pattern detectorif all efforts fail.

Having detected the objects in a webpage, the function-based objectmodels can now be generated.

Basic Function Object Model Generation for a Basic Object

The functional properties of a basic object are generally included inits HTML source content. Hence, by examining the HTML source content,the functional properties of the basic objects can be ascertained. Inthe specific HTML context, such can be accomplished by defining somebasic rules and then programmatically using the rules to identify thefunctional properties. The following discussion describes some specificrules that pertain to, in this specific context, generation of a basicfunction-based object model for a basic object.

-   -   The presentation property can be determined by analyzing the        HTML source and tags to extract the Media Type, Encoding Format        and Layout information of an object.    -   The semanteme property can be determined by analyzing the        content itself to extract the semantic layer.    -   The navigation property is the destination of a hyperlink        contained in a basic object.    -   The decoration property varies between [0,1] according to the        presentation and semanteme properties. Text/Video objects        normally have a lower decoration value. The following objects        generally have higher values to indicate that their main purpose        is for decoration: general decoration symbols, lines and        separators between objects, and objects with a “Background”        property in an HTML tag.    -   The interaction property of a basic object can be one of the        following three categories:        -   Button for Object with the <button> tag and/or some            button-like selection list.        -   Input Text for Object with <Input . . . > or related tags.        -   Display for interaction property of other Objects.

Basic Function Object Model Generation for a Composite Object

The following are some basic rules, in this specific context, forgenerating the basic function-based object model of a composite object:

-   -   The clustering relationship can be one of the following three        categories:        -   Complement: the root children are neighbors and have one or            more different basic properties (such as Presentation or            Semantic Layer).        -   Parallel: the root children are neighbors and have similar            basic properties.        -   Table: the root children have a table tag and 2-dimensional            clustering headers (column and row header).    -   Presentation Relationship        -   Time Order: generally no time sequence unless required by            the Object.        -   Space Order can be determined by analyzing the visual image            of the content.        -   Root children are generally separable except special cases            (such as Object for input).

Specific Function-Based Object Model Generation

Specific Function-Based Object Model Generation for a Basic Object

As described above, the specific function-based object model representsan object with its category. For a basic object, its category is mainlydetermined by the major properties of the basic object and theproperties of the father/brother objects. In the illustrated anddescribed embodiment, a rule-based decision tree is applied to determinethe category of basic object.

As an example of a rule-based decision tree that can be utilized toascertain the category of a basic object, consider FIG. 5.

Step 500 determines whether the basic object comprises a hyperlink. Ifit does, then step 502 determines whether the basic object comprises ahyperlink to another object. If the basic object is not a hyperlink toanother object, then step 504 categorizes the basic object as anavigation basic object that links to another application. If, on theother hand, step 502 determines that the hyperlink is a link to anotherobject, then step 506 determines whether the object is a root child of acomposite object. If the object is a root child of a composite object,then step 508 categorizes the object as a navigation basic object. If,on the other hand, the object does not comprise a root child of acomposite object, then step 510 determines whether the object is aspecial function object. If so, then step 514 categorizes the object asa special function object. If the object is not a special functionobject, then step 512 categorizes the object as an independentnavigation object.

If, at step 500, the object is not determined to be a hyperlink, thenstep 516 determines whether the object comprises long text, largeimages, audio or video, or the like. If so, step 518 categorizes theobject as an information object. If, on the other hand, none of thesecriteria are met, then step 520 determines whether the object comprisesa radio button, input box, select box or the like. If the object doescomprise one of these items, step 522 categorizes the object as aspecial control. If, on the other hand, the object does not comprise oneof these items, step 524 determines whether the object comprises adecoration property. If not, then step 526 categorizes the object as aninformation object. If the object does comprise a decoration property,then step 528 categorizes the object as a decoration object, symbol,line or the like.

Specific Function-based Object Model Generation for a Composite Object

The category of a composite object can be determined by the majorproperties of the composite object and/or its root children, as well asthe application environment. Each different category can utilize aspecific detection method that is specifically drawn along lines thatare associated with that category. The specific detection methods canaccordingly include one or more rules against which the various objectsare tested to ascertain their category.

In the discussion that follows, and to assist the reader in appreciatingthis aspect of the described embodiments, two specific examples aregiven. The first example pertains to detecting and categorizing a normalnavigation bar, and the second example pertains to detecting andcategorizing a page. As will be appreciated and understood by those ofskill in the art, the general principles of the examples about to bedescribed can be extended to other categories.

Example 1 Navigation Bar Detection

According to its media type, a normal navigation bar can be classifiedas either a “text” normal navigation bar or an “image” normal navigationbar. In this specific example, the focus will be on rules that detect atext normal navigation bar. Of course, an image normal navigation barcan also be detected with a similar method.

To ascertain whether a navigation bar is a text normal navigation bar ina website, the following rules can be employed.

Rules for Text Normal Navigation Bar (NNB) Rule 1 Most of the rootchildren of a Text NNB should be navigation objects. That is:(N_(N)/N_(R)) should be not less than H_(min), where N_(N) is the totalnumber of navigational root children, and N_(R) is the total number ofroot children. Rule 2 Root children text length should be less thanL_(max). Rule 3 Text NNB appearance times in the website should be notless than R_(min). Rule 4 Root children of a Text normal navigation barshould have similar properties. Rule 5 Root children of a Text normalnavigation bar should have hyperlinks all to either outside or inside,only a small percentage of deviation D_(max) is allowed.

The constant variables above such as H_(min), L_(max), R_(min) andD_(max) are variable values that can vary in different websitesaccording to the practical detection result.

Based on the rules above, a detection algorithm can be easilyprogrammed. Small deviations can be allowed for the binary conditions inpractical detection. That is, even if one of the values is slightly onthe wrong side of a threshold, the corresponding text normal navigationbar can be accepted if all the other values are well away from theirthresholds.

Example 2 Page Category Detection

As described above, a web page has two basic categories: Index Page andContent Page. Presented here is a hyperlink-based page categorydetection method, which is effective for all languages based on XML.

In accordance with this method, the so-called “out degree” and “indegree” of a web page are defined. The out degree is the number ofhyperlinks inside the page. The in degree is the number of web pageswith hyperlinks to the current page in the whole website.

Using statistical analysis, it has been ascertained that a page with arelatively large out degree or in degree may be an index page, and apage with a relatively small out degree and in degree may be a contentpage. That is, for a given page with an out degree (OD) and an in degree(ID), the following rules can be used:

-   -   If OD>OD0 or ID>ID0, the page can be considered as an Index        Page; and    -   If OD<OD0 and ID<ID0, the page can be considered as a Content        Page,    -   where, OD0 and ID0 are two constant variables determined by the        website.

To find OD0 and ID0, we first sort the pages by OD and ID in descendingorder, respectively, and graph a corresponding OD(i)-i and ID(i)-idiagram of a website (i is the ordered number of a web page).

FIG. 6 gives an example of an OD(i)-i and ID(i)-i diagram for Yahoo'sChinese news website (1,615 pages in all). By statistical analysis ofmany websites, it has been determined that OD0 and ID0 correspond to theinflexion points in the OD(i)-i and ID(i)-i diagram as shown in FIG. 6.

Once the graphs of the corresponding OD(i)-i and ID(i)-i are made, thereare two methods that have been found useful to ascertain OD0 and ID0.

The first method is referred to as a “beeline simulation”, and is bestunderstood in connection with FIG. 7. There, the graphed diagram issimulated with two beelines 700, 702. That is, the average distancebetween the beelines and the original curve of OD is minimized. Then theOD0 is calculated as the y-coordinate of the intersection of the lines700, 702.

The second method is referred to as a polynomial simulation and is bestunderstood with reference to FIG. 8. There, the graphed diagram issimulated with a polynomial curve 800 (second power or more). That is,the average distance between the polynomial and the original curve of ODis minimized. Then, the y-coordinate of the inflexion with the largestcurvature of the polynomial curve is designed as OD0.

Exemplary Method

FIG. 9 is a flow diagram that describes steps in a method in accordancewith the above-described embodiments. The method can be implemented inconnection with any suitable hardware, software, firmware or combinationthereof. In the illustrated and described example, the method isimplemented in software. The method can be implemented by, among othertypes of computing devices, suitably configured client devices, as wellas suitably configured servers that serve up web pages to clientdevices.

Step 900 detects one or more objects that comprise a web page. Exemplaryobjects are described above in the form of basic objects and compositeobjects. The exemplary objects are not intended to limit the objectsthat can be detected, or the object types that can be detected. Rather,the specifically discussed and described basic and composite objects aresimply given as examples to illustrate the inventive approach. Inaddition, the objects can be detected in any suitable way. Specificexamples of how this can be done in but one specific context are given.It is to be understood and appreciated that these specific examples arenot to limit application of the claimed subject matter to eitherspecific detection paradigms or detection of particular types of objects(e.g. HTML objects). Once detected, step 902 ascertains functionalproperties associated with any basic objects or first object types.Non-limiting examples of how this can be done are given above. Step 904ascertains functional properties associated with any composite objectsor second object types. Non-limiting examples of how this can be doneare given above.

Step 906 generates basic function-based object models for any of thebasic objects. Non-limiting examples of how this can be done are givenabove. Step 908 generates basic function-based object models for anycomposite objects. Non-limiting examples of how this can be done aregiven above. Step 910 generates specific function-based object modelsfor any basic objects. Non-limiting examples of how this can be done aregiven above. Step 912 generates specific function-based object modelsfor any composite objects. Non-limiting examples of how this can be doneare given above. Step 914 then uses the function-based object models toadapt web content. Example of how this step can be implemented are givenbelow.

Experimental Example

The following is an example of experiment results that were generatedusing an English news website. In this example, the total number of webpages was 73, in which the number of Index/Content Pages was 5/68respectively. The OD0=22, ID0=4. Based on the algorithm above, we canget the function of all the web pages.

FIGS. 10 and 11 give examples of an Index Page (OD=36, ID=76) and aContent Page (OD=8, ID=3) in the website of this example. Sincenavigation bars may exist in both Index Pages and Content Pages, we cantake them away from web pages before calculating the OD and ID of eachpage to eliminate the influence of the navigation bar. Using theabove-described method, higher precisions for page category detectionhave been achieved over past methods, such as the one described inPirolli et al., Silk from a Sows Ear. Extracting Useable Structures fromthe Web, Proc. CHI'96, 1996, pp. 118-125. Moreover, compared with otherapproaches, the described method has not only a higher precision butalso better extensibility.

Content Adaptation Based on Function-Based Object Models

For practical adaptation, the described function-based object modelapproach can be employed in connection with some guidelines. Thediscussion below presents some general rules based on the basicfunction-based object model. In addition, some specific rules for webadaptation over WAP (Wireless Application Protocol), based on thespecific function-based object model are illustrated as well.

To provide users with the same basic browsing experience, the followingbasic criterion have been found useful:

-   -   Place the adapted content in the same time and space order as        the original content to keep the same visual browsing        experience.    -   Try to align the children of a composite object together to keep        the content integrality.    -   Keep the original layer hierarchy to make the content structure        clear.

General Adaptation Rules Based on the Basic Function-Based Object Model

The following rules are exemplary rules that can be used in connectionwith the basic function-based object model, and are provided as examplesonly.

-   -   The presentation property should be considered together with        device capability and language difference to generate the most        suitable Media Type, Encoding Format and Layout Format for an        Object.    -   The semanteme property helps to select the most appropriate        semantic layer of an object.    -   Decoration values of different objects can be compared to decide        whether an object should be removed. Such can be decided by a        decision engine, such as the one discussed in Chen et al., An        Adaptive Web Content Delivery System, Proc. AH2000, Springer,        2000, pp. 284-If the decoration value is 0, then the object        should be retained. Otherwise, the object can be removed if        necessary.    -   Rules for the hyperlink property include (1) an object should be        retained if it has a hyperlink to another Object; and (2) an        object should be retained if it has a hyperlink to an        unsupported application.    -   Rules for the interaction property include:        -   Display: retain or substitute the object according to the            actual situation.        -   Submit/Query: the object should be retained, discarded or            substituted with its brother objects as a whole according to            the actual situation.    -   Rules for the clustering property (for composite objects only):        -   Complement: the composite object can be divided into several            objects in different layers if they are separable. Such is            diagrammatically represented in FIG. 12. This rule is            reversible.        -   Parallel: the composite object can be divided into several            parts at its root children level, as shown in FIG. 13, if            they are separable. This rule is reversible.        -   Table: The composite object can be divided into several            sub-tables along column (row) dimensions as shown in FIG. 14            (the original table is in the middle). Each sub-table            contains the column (row) header and one or several rows            (columns) of the table.

Web Adaptation over WAP Based on the Specific Function-Based ObjectModel

The rules described above are just basic guidelines and should not beconstrued as limiting in any sense. They can be combined with specificrules based on the specific function-based object model and applicationenvironment for content adaptation.

To assist the reader in further understanding and appreciating theadaptation process in the WAP context, and especially in view ofexemplary specific rules based on a specific function-based objectmodel, the following example is given.

The WAP environment is quite different from that of the web.Specifically, the WAP environment requires content re-authoring andtruncation to enable WAP users to browse the web content on suitablyconfigured devices. Additionally, the narrow bandwidth, small memory,different protocol and poor presentation capability (e.g. small screensize, poor support for multimedia, etc.) of WAP devices typicallyprohibit the delivery of normal web content and web pages originallydesigned for desktops. To address these problems, web content or webpages are divided into several “decks” for WAP devices. A deck is simplya sub-division of the web content or page at some level of granularity.These considerations make web content adaptation over WAP asignificantly difficult problem to solve.

The following are some exemplary specific rules that can be used for WAPadaptation based on a specific function-based object model.

With respect to the navigation bar in index pages, since index pagesmainly serve as navigation guides, the navigation bar should beretained. Text normal navigation bars can be retained without change.Image normal navigation bars, Frames, Menus or Maps should be convertedinto Text normal navigation bars. With respect to the navigation bar incontent pages, since the purpose of a content page is to deliversemantic information, the navigation bar can be discarded. Otherwise,the small screens of WAP devices can be filled with redundantinformation.

Navigation lists can be retained. Normal List/Information andList/Introduction Lists can be retained without change. With respect tomaps, such should be converted to a hyperlink text list.

Independent navigation lists can be retained.

User Query/User Submit should be retained as a whole, and the serverside program can be revised to adapt to the WAP environment.

With respect to the decoration object, highlights can be replaced withbig font text. Separators, list leaders, and background can all bediscarded.

Special objects such as AD, Logo, Contact, Copyright, Reference, and thelike, can be discarded or changed to a text form according to author'sintention.

In addition to the specific adaptation rules described above, there arealso language conversion rules (e.g. from HTML to WML). Four basic rulesthat can be used include:

-   -   HTML Tags with similar syntax in WML are retained without        change, e.g., <p>, <u>, <i>, <strong>, <em>, <big>, <small>,    -   HTML Tags which can be replaced by one or several related WML        Tags are converted into the corresponding WML Tags, e.g., <ul> .        . . </ul> to <p> . . . </p>, . . .    -   HTML Tags which are invalid in WML are discarded, e.g., <embed>,        <applet>, . . .    -   Complex HTML Tags are converted into a set of related WML Tags        according to actual situation, e.g., <table>,

In order to assist users in locating information quickly, the mostimportant information should be delivered first. This can be achieved byreorganizing the web content into WML decks. A couple of exemplary decksare described in more detail below.

Exemplary Specific Architecture for WAP Adaptation

FIG. 15 illustrates an exemplary system architecture 1500 that can beutilized for WAP adaptation. Architecture 1500 is desirably implementedin software. An object & page analysis module 1502 generates afunction-based object model for an original website 1504 using thetechniques described above. A content adaptation module 1506 makesadaptations according to function-based object model-based adaptationrules 1508 and, where employed, language conversion rules 1510. Suchproduces web-adapted content in the form of a new WAP site 1512.

Adaptation Example

FIG. 10 shows an adaptation example for an Index Page 1000, in whichcontent with unsupported media types are removed, and several new decks1002-1014 are generated to show the original content at differentlayers. An index deck 1002 is an outline of the original page 1000.Detailed content resides in Deck 1-6 (i.e. decks 1004-1014). FIG. 16shows the adaptation result in a WAP simulator

FIG. 17 shows an adaptation result of a Content Page 1700, in whichredundant content is removed, and the original page 1700 is divided intotwo decks 1702, 1704 because of the memory limitation of WAP devices.

Exemplary Computer Environment

The embodiments described above can be implemented in connection withany suitable computer environment. Aspects of the various embodimentscan, for example, be implemented, in connection with server computers,client computers/devices, or both server computers and clientcomputers/devices. As but one example describing certain components ofan exemplary computing system, consider FIG. 18.

FIG. 18 illustrates an example of a suitable computing environment 1800.It is to be appreciated that computing environment 1800 is only oneexample of a suitable computing environment and is not intended tosuggest any limitation as to the scope of use or functionality of theinventive embodiments. Neither should the computing environment 1800 beinterpreted as having any dependency or requirement relating to any oneor combination of components illustrated in the exemplary computingenvironment 1800.

The inventive techniques can be operational with numerous other generalpurpose or special purpose computing system environments orconfigurations. Examples of well known computing systems, environments,and/or configurations that may be suitable for use with the inventivetechniques include, but are not limited to, personal computers, servercomputers, thin clients, thick clients, hand-held or laptop devices,multiprocessor systems, microprocessor-based systems, set top boxes,programmable consumer electronics, network PCs, minicomputers, mainframecomputers, distributed computing environments that include any of theabove systems or devices, and the like.

In certain implementations, the inventive techniques can be described inthe general context of computer-executable instructions, such as programmodules, being executed by a computer. Generally, program modulesinclude routines, programs, objects, components, data structures, etc.that perform particular tasks or implement particular abstract datatypes. The inventive techniques may also be practiced in distributedcomputing environments where tasks are performed by remote processingdevices that are linked through a communications network. In adistributed computing environment, program modules may be located inboth local and remote computer storage media including memory storagedevices.

In accordance with the illustrated example embodiment of FIG. 18computing system 1800 is shown comprising one or more processors orprocessing units 1802, a system memory 1804, and a bus 1806 that couplesvarious system components including the system memory 1804 to theprocessor

Bus 1806 is intended to represent one or more of any of several types ofbus structures, including a memory bus or memory controller, aperipheral bus, an accelerated graphics port, and a processor or localbus using any of a variety of bus architectures. By way of example, andnot limitation, such architectures include Industry StandardArchitecture (ISA) bus, Micro Channel Architecture (MCA) bus, EnhancedISA (EISA) bus, Video Electronics Standards Association (VESA) localbus, and Peripheral Component Interconnects (PCI) buss also known asMezzanine bus.

Computer 1800 typically includes a variety of computer readable media.Such media may be any available media that is locally and/or remotelyaccessible by computer 1800, and it includes both volatile andnon-volatile media, removable and non-removable media.

In FIG. 18, the system memory 1804 includes computer readable media inthe form of volatile, such as random access memory (RAM) 1810, and/ornon-volatile memory, such as read only memory (ROM) 1808. A basicinput/output system (BIOS) 1812, containing the basic routines that helpto transfer information between elements within computer 1800, such asduring start-up, is stored in ROM RAM 1810 typically contains dataand/or program modules that are immediately accessible to and/orpresently be operated on by processing unit(s)

Computer 1800 may further include other removable/non-removable,volatile/non-volatile computer storage media. By way of example only,FIG. 18 illustrates a hard disk drive 1828 for reading from and writingto a non-removable, non-volatile magnetic media (not shown and typicallycalled a “hard drive”), a magnetic disk drive 1830 for reading from andwriting to a removable, non-volatile magnetic disk 1832 (e.g., a “floppydisk”), and an optical disk drive 1834 for reading from or writing to aremovable, non-volatile optical disk 1836 such as a CD-ROM, DVD-ROM orother optical media. The hard disk drive 1828, magnetic disk drive 1830,and optical disk drive 1834 are each connected to bus 1806 by one ormore interfaces 1826.

The drives and their associated computer-readable media providenonvolatile storage of computer readable instructions, data structures,program modules, and other data for computer 1800. Although theexemplary environment described herein employs a hard disk 1828, aremovable magnetic disk 1832 and a removable optical disk 1836, itshould be appreciated by those skilled in the art that other types ofcomputer readable media which can store data that is accessible by acomputer, such as magnetic cassettes, flash memory cards, digital videodisks, random access memories (RAMs), read only memories (ROM), and thelike, may also be used in the exemplary operating environment.

A number of program modules may be stored on the hard disk 1828,magnetic disk 1832, optical disk 1836, ROM 1808, or RAM 1810, including,by way of example, and not limitation, an operating system 1814, one ormore application programs 1816 (e.g., multimedia application program1824), other program modules 1818, and program data 1820. Some of theapplication programs can be configured to present a user interface (UI)that is configured to allow a user to interact with the applicationprogram in some manner using some type of input device. This UI istypically a visual display that is capable of receiving user input andprocessing that user input in some way. Such a UI may, for example,comprises one or more buttons or controls that can be clicked on by auser.

Continuing with FIG. 18, a user may enter commands and information intocomputer 1800 through input devices such as keyboard 1838 and pointingdevice 1840 (such as a “mouse”). Other input devices may include aaudio/video input device(s) 1853, a microphone, joystick, game pad,satellite dish, serial port, scanner, or the like (not shown). These andother input devices are connected to the processing unit(s) 1802 throughinput interface(s) 1842 that is coupled to bus 1806, but may beconnected by other interface and bus structures, such as a parallelport, game port, or a universal serial bus (USB).

A monitor 1856 or other type of display device is also connected to bus1806 via an interface, such as a video adapter 1844. In addition to themonitor, personal computers typically include other peripheral outputdevices (not shown), such as speakers and printers, which may beconnected through output peripheral interface 1846.

Computer 1800 may operate in a networked environment using logicalconnections to one or more remote computers, such as a remote computer1850. Remote computer 1850 may include many or all of the elements andfeatures described herein relative to computer 1800.

As shown in FIG. 18, computing system 1800 can be communicativelycoupled to remote devices (e.g., remote computer 1850) through a localarea network (LAN) 1851 and a general wide area network (WAN) 1852. Suchnetworking environments are commonplace in offices, enterprise-widecomputer networks, intranets, and the Internet.

When used in a LAN networking environment, the computer 1800 isconnected to LAN 1851 through a suitable network interface or adapter1848. When used in a WAN networking environment, the computer 1800typically includes a modem 1854 or other means for establishingcommunications over the WAN 1852. The modem 1854, which may be internalor external, may be connected to the system bus 1806 via the user inputinterface 1842, or other appropriate mechanism.

In a networked environment, program modules depicted relative to thepersonal computer 1800, or portions thereof, may be stored in a remotememory storage device. By way of example, and not limitation, FIG. 18illustrates remote application programs 1816 as residing on a memorydevice of remote computer It will be appreciated that the networkconnections shown and described are exemplary and other means ofestablishing a communications link between the computers may be used.

CONCLUSION

Compared to other approaches, the inventive approach described above hasmore satisfactory results and brings the same consistent browsingexperience to users. Since an author's intention is well understoodthrough the function-based object model analysis, the content adaptationis quite reasonable. For example, page function analysis (index/contentpage) has helped the decision making process, in WAP and otherscenarios, as to whether to keep a navigation bar or not. Since themajor purpose of an index page is to provide a navigation guide tousers, the navigation bar is retained in the index page. On thecontrary, the major purpose of the content page is to provideinformation to users, and, hence, the navigation bar can be consideredas redundant information, and is therefore removed.

Another example is the generation of an index deck, as in FIG. 10. Thesystem first detects the navigation lists in the index page throughfunction-based object model analysis. At the same time, the parallelclustering relationship of these navigation lists is also detected. Thesystem then extracts the abstract information from these navigationlists, and lists them as “peers” to generate the new index deck, which,in turn, enables users to navigate the adapted content easily.

The described methods and systems are advantageously adaptable todifferent various websites because of the general nature of theapproach. That is, the described embodiments can be based on visualinformation and functional property analysis instead of tag analysis. Asa result, the methods are not only able to handle HTML based websites,but can also be easily extended to other web environment such as DHTMLbased websites (as set forth in the W3C).

Although the invention has been described in language specific tostructural features and/or methodological steps, it is to be understoodthat the invention defined in the appended claims is not necessarilylimited to the specific features or steps described. Rather, thespecific features and steps are disclosed as preferred forms ofimplementing the claimed invention.

1. A web content adaptation method comprising: analyzing one or morefunctions associated with a webpage; and adapting the webpage forpresentation on a device based on said analyzing.
 2. The method of claim1, wherein said analyzing comprises generating one or morefunction-based object models that represent objects comprising thewebpage.
 3. The method of claim 2, wherein said generating comprises:identifying one or more basic objects associated with the webpage, basicobjects comprising a smallest information body that cannot be furtherdivided; and identifying one or more composite objects associated withthe webpage, composite objects comprising objects that contain otherobjects.
 4. The method of claim 1, wherein said adapting comprises doingso in view of one or more networking conditions.
 5. The method of claim1, wherein said adapting comprises doing so in view of one or more userpreferences.
 6. A web content adaptation method comprising: analyzingone or more functions associated with a webpage that is configured forpresentation within a first client environment; and based on saidanalyzing, adapting the webpage for presentation within a second clientenvironment that is different from the first client environment.
 7. Themethod of claim 6, wherein said analyzing comprises generating one ormore function-based object models that represent objects comprising thewebpage.
 8. The method of claim 7, wherein said generating comprises:identifying one or more basic objects associated with the webpage, basicobjects comprising a smallest information body that cannot be furtherdivided; and identifying one or more composite objects associated withthe webpage, composite objects comprising objects that contain otherobjects.
 9. The method of claim 8, wherein said generating furthercomprises generating said one or more function-based object models as afunction of properties that are associated with said one or more basicobjects and said one or more composite objects.
 10. The method of claim9, wherein said adapting comprises applying one or more rules to saidone or more function-based object models.
 11. The method of claim 6,wherein said first and second client environments pertain to differentclient devices.
 12. The method of claim 6, wherein said first and secondclient environments pertain to different types of client devices. 13.The method of claim 6, wherein said first and second client environmentspertain to different network conditions.
 14. The method of claim 6,wherein said first and second client environments pertain to differentuser preferences.
 15. One or more computer-readable media havingcomputer-readable instructions thereon which, when executed by one ormore processors, cause the one or more processors to implement themethod of claim
 6. 16. A web content adaptation method that adapts webcontent from one format to another, and which uses multiplefunction-based object models to do so, where the function-based objectmodels comprise models that pertain to (1) basic objects that comprise asmallest information body that cannot be further divided, and (2)composite objects that comprise objects that can contain other objects.17. The web content adaptation method of claim 16, wherein thefunction-based object models are generated as a function of one or moreproperties associated with the objects.
 18. A system for adapting webcontent from one format to another comprising one or more function-basedobject models, individual function-based object models representingobjects that are present in a webpage in terms of one or more of anobject's functional properties.
 19. The system of claim 18, wherein oneof the properties comprises a presentation property that defines a wayin which the object is presented.
 20. The system of claim 18, whereinone of the properties comprises a semanteme property associated with thecontent of an object.
 21. The system of claim 18, wherein one of theproperties comprises a decoration property pertaining to the extent towhich an object serves to decorate a webpage.
 22. The system of claim18, wherein one of the properties comprises a hyperlink propertypertaining to an object to which another object points via a hyperlink.23. The system of claim 18, wherein one of the properties comprises ainteraction property pertaining to an interaction method of an object.24. The system of claim 18, wherein one of the properties comprises aclustering relationship property pertaining to a relationship among anyroot children of an object.
 25. The system of claim 18, wherein one ofthe properties comprises a presentation relationship property pertainingto a presentation order associated with any root children of an object.26. Software code embodied on a computer-readable medium that implementsthe system of claim
 18. 27. A computer architecture for use in adaptingweb content for display on a computing device, the architecturecomprising: an analysis module for receiving at least one webpage andprocessing the one webpage to produce one or more function-based objectmodels that describe functional properties of objects that are containedin the one webpage; one or more rules modules that contain rules thatare to be used to adapt content contained in the webpage; and a contentadaptation module configured to process the one or more function-basedobject models in accordance with one or more rules contained in the oneor more rules modules to produce a new web page that has been adaptedfrom the one web page.
 28. The computer architecture of claim 27,wherein the content adaptation module is configured to produce a new webpage for display on a WAP-enabled device.
 29. The computer architectureof claim 27, wherein said analysis module is configured to producefunction-based object models that pertain to both basic objects andcomposite objects, basic objects comprising a smallest information bodythat cannot be further divided; and composite objects comprising objectsthat contain other objects.
 30. The computer architecture of claim 29,wherein said analysis module is configured to produce, for basicobjects, function-based object models that comprise values associatedwith the following properties: (1) a presentation property that definesa way in which the object is presented, (2) a semanteme propertyassociated with content of an object, (3) a decoration propertypertaining to an extent to which the basic objects serves to decoratethe webpage, (4) a hyperlink property pertaining to an object to whichthe basic object points via a hyperlink, and (5) a interaction propertypertaining to an interaction method of the basic object.
 31. Thecomputer architecture of claim 29, wherein said analysis module isconfigured to produce, for composite objects, function-based objectmodels that comprise values associated with the following properties:(1) a clustering relationship property pertaining to a relationshipamong root children of the composite object, and (2) a presentationrelationship property pertaining to a presentation order associated withthe root children of the composite object.